2003
DOI: 10.5194/angeo-21-103-2003
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Near Real Time SLA and SST products during 2-years of MFS pilot project: processing, analysis of the variability and of the coupled patterns

Abstract: Abstract. The Near Real Time (NRT) operational products developed from satellite data (AVHRR, Topex/Poseidon, Ers-2) in the framework of the Mediterranean Forecasting System Pilot Project (MFSPP, autumn 1998(MFSPP, autumn -autumn 2000 are described and compared to delayed time products over the Mediterranean sea. MFSPP SLA and SST data are then discussed in the general context of the Mediterranean circulation, showing the interannual variability of the fields and identifying recurrent or anomalous features a… Show more

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Cited by 24 publications
(11 citation statements)
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“…Our previous experience with satellite sea surface temperature interpolation showed that even if OI can reduce the level of noise in L4 fields (depending on the signal covariance characteristic scales, OI actually works also as a smoother), it is much more efficient to work with a slightly smaller amount of data of high quality, rather than including suspicious data into an analysis system (Buongiorno Nardelli et al, 2003;Marullo et al, 2007;Buongiorno Nardelli et al, 2010;Buongiorno Nardelli et al, 2013;Buongiorno Nardelli et al, 2015). Outliers found in proximity of data gaps, in particular, have a dramatic impact on the accuracy of the retrieval and are better removed before carrying out any interpolation.…”
Section: 4 Input Data Pre-processingmentioning
confidence: 98%
“…Our previous experience with satellite sea surface temperature interpolation showed that even if OI can reduce the level of noise in L4 fields (depending on the signal covariance characteristic scales, OI actually works also as a smoother), it is much more efficient to work with a slightly smaller amount of data of high quality, rather than including suspicious data into an analysis system (Buongiorno Nardelli et al, 2003;Marullo et al, 2007;Buongiorno Nardelli et al, 2010;Buongiorno Nardelli et al, 2013;Buongiorno Nardelli et al, 2015). Outliers found in proximity of data gaps, in particular, have a dramatic impact on the accuracy of the retrieval and are better removed before carrying out any interpolation.…”
Section: 4 Input Data Pre-processingmentioning
confidence: 98%
“…In particular, mapped AVHRR SST fields are computed only with night-time passages of NOAA-AVHRR-14 and NOAA-AVHRR-15 satellite (Marullo et al, 2007;Buongiorno et al, 2003).…”
Section: Appendix a Assimilated Datamentioning
confidence: 99%
“…The Mediterranean Sea and Black Sea L4 SST products developed by the Consiglio Nazionale delle Ricerche-Istituto di Scienze dell'Atmosfera e del Clima-Gruppo di Oceanografia da Satellite (CNR-ISAC-GOS) within MyOcean projects, as well as in previous projects/research activities, have been obtained directly through a space-time OI approach (Buongiorno Nardelli, Colella, Santoleri, Guarracino, & Kholod, 2010;Buongiorno Nardelli, Tronconi, Pisano, & Santoleri, 2013;Buongiorno Nardelli et al, 2003;Marullo, Buongiorno Nardelli, Guarracino, & Santoleri, 2007;Santoleri, Marullo, & Böhm, 1991).…”
Section: Introductionmentioning
confidence: 99%